TECHNOLOGY/BUSINESS OPPORTUNITY A system to cryptographically distinguish between human-generated text vs. AI-generated text

Opportunity: Lawrence Livermore National Laboratory (LLNL), operated by the Lawrence Livermore National Security (LLNS), LLC under contract no. DE-AC52-07NA27344 (Contract 44) with the U.S. Department of Energy (DOE), is offering the opportunity to enter into a collaboration to further develop and commercialize its novel system to cryptographically distinguish between human-generated text vs. AI-generated text. Background: Generative Artificial Intelligence (AI) is undergoing rapid development and threatening to upend norms on the internet and in classrooms. Generative AI programs such as ChatGPT can write text (and other data) that is largely indistinguishable from text generated by humans. Unlike humans, however, AI can generate text at volumes and speeds that are many orders of magnitude larger than what a single human could achieve. At the same time, AI-generated text is of variable quality. There is a risk that AI-generated text will come to dominate online text and discourse while drowning out text generated with the thought and attention of actual humans. This has the potential to drown out the voices, opinions, and thinking of real humans while simultaneously enabling the proliferation of online deception and manipulation (for example: fake news or fake opinions). A growing public concern is that generative AI can be used to cheat on essay assignments in education and evaluation settings, impersonate a human in validation or authentication security controls, or be misused for other unethical or even illegal reasons. Description: LLNL has invented a new system that uses public key cryptography to differentiate between human-generated text and AI-generated text. This invention can be used to validate that text is likely to be human generated for the purposes of sorting or gatekeeping on the internet, can detect cheating on essay assignments, and can be used as an automatic captcha that does away with the hassle of traditional captchas. This invention validates that typed data (text) is likely to have been generated by a human and not by a generative AI. This validation process produces an anonymized digital signature to attest to the fact that the text was human generated. The digital signature can be attached to the text as metadata and verified by third parties. The digital signature can also contain data related to the timespan and history over which the text was typed, the app or context in which the text was typed, and in certain applications identifying information about who typed the text. The digital signature verification can be easily checked by third party websites. Websites can then use this verification that the text was likely human generated to prioritize, curate, or gatekeep (e.g., prevent AI generated text from getting in). Advantages/Benefits: The primary advantage of LLNL's novel system is that it enables validation that text was human-generated. This advantage can be used to implement new cybersecurity controls and to build trust in generative AI applications. Potential Applications: Human-verification for authentication and identity management systems, with added features of auto-generated digital signatures if desired Gatekeeping for operational technologies and control systems Detecting AI-generated text, such as for education, evaluation purposes or journalism industries Automates human-input verification for search engines and web forms (instead of the hassle typically associated with current captchas where picture puzzles must be solved). Works in a fully anonymized fashion. It can also be linked to a fingerprint scanner or other biometrics (e.g., keystroke dynamics analysis) in select applications where verified identity is required. Development Status: Current stage of technology development: TRL 2 (March 2023) LLNL has filed for patent protection on this invention. LLNL is seeking industry partners with a demonstrated ability to bring such inventions to the market. Moving critical technology beyond the Laboratory to the commercial world helps our licensees gain a competitive edge in the marketplace. All licensing activities are conducted under policies relating to the strict nondisclosure of company proprietary information. Please visit the IPO website at https://ipo.llnl.gov/resources for more information on working with LLNL and the industrial partnering and technology transfer process. Note: THIS IS NOT A PROCUREMENT. Companies interested in commercializing LLNL's novel system to cryptographically distinguish between human-generated text vs. AI-generated text should provide an electronic OR written statement of interest, which includes the following: Company Name and address. The name, address, and telephone number of a point of contact. A description of corporate expertise and/or facilities relevant to commercializing this technology. Please provide a complete electronic OR written statement to ensure consideration of your interest in LLNL's novel system to cryptographically distinguish between human-generated text vs. AI-generated text. The subject heading in an email response should include the Notice ID and/or the title of LLNL's Technology/Business Opportunity and directed to the Primary and Secondary Point of Contacts listed below. Written responses should be directed to: Lawrence Livermore National Laboratory Innovation and Partnerships Office P.O. Box 808, L-779 Livermore, CA 94551-0808 Attention: IL-13820